Senior Machine Learning Engineer - Accelerating Drug Discovery with AI

Key Responsibilities:

• Maintain and improve data ingestion and processing pipelines for scalability, reproducibility, reliability, and speed
• Improve the training and inference speeds of a large class of ML models including transformer-based architectures, structured state-space models, graph neural networks, and many others
• Design, implement, and deploy ways to make complex deep learning models usable by biologists and other domain specialists
• Manage ML infrastructure, both on premises and in the cloud
• Rapidly prototype POCs in partnership with ML scientists and other stakeholders
• Test models at scale and ensure CI/CD best practices are followed by the whole team

Basic Qualifications:

• 3+ years of experience
• Expertise in ML frameworks (e.g., PyTorch, TensorFlow)
• Strong background in distributed systems and containerization
• Self-motivated problem-solver with excellent communication skills
• Adaptability to evolving requirements in a fast-paced field
• Ability to mentor and elevate team members' skills

Preferred Qualifications:

• Previous startup experience bringing ML prototypes to production
• Familiarity with bioinformatics data/pipelines
• Knowledge of MLFlow, Kubeflow, Ray, Dask, Fluidstack, or similar tools

What we offer:

• A highly competitive salary, a meaningful equity ownership stake in Deep Genomics, and exceptional opportunities for learning and growth
• Company paid benefits
• Exceptional opportunities for learning and growth in a world-class team of researchers and software developers, working at the intersection of the most exciting areas of science and technology